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LangGraph · LLM observability
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Debugs LangChain and LangGraph agents by pulling recent execution traces with the langsmith-fetch CLI and reporting errors, tool calls, timings and token use. | ComposioHQ/ | 77k | 8 repos | ~2.7k | Automated safety check: Pass | No licence | 23 days ago |
| 2 | Helps instrument a custom Python or TypeScript agent to record events for Failproof AI, verify what gets written, and run an evaluator worker that scores the runs. | FailproofAI/ | 5.3k | — | ~6k | Automated safety check: Pass | Unknown | 4 days ago |
| 3 | Enhancement-overlay skill — the DECISION + WIRING layer for LM observability that the single-backend skills [[langsmith]], [[phoenix]], [[mlflow]] do NOT cover. | agentsope/ | 436 | — | ~4.4k | Automated safety check: Pass | MIT | 2 days ago |
| 4 | INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. | langchain-ai/ | 1.3k | — | ~3.6k | Automated safety check: Pass | MIT | 2 days ago |
| 5 | A skill your agent uses when you need to test or evaluate LangGraph/LangChain agents: writing unit or integration tests, generating test scaffolds, mocking LLM/tool behavior, running trajectory… | soba-labs/ | 107 | — | ~2.3k | Automated safety check: Pass | MIT | 1 mo ago |
| 6 | Trace, evaluate, and deploy AI agents and LLM applications with LangSmith. | langchain-ai/ | 426 | — | ~935 | Automated safety check: Pass | MIT | yesterday |
| 7 | Deploy and operate production agent servers with LangSmith Deployment. | soba-labs/ | 107 | — | ~1.7k | Automated safety check: Pass | MIT | 1 mo ago |
| 8 | INVOKE THIS SKILL when building, testing, or deploying Managed Deep Agents in LangSmith. | langchain-ai/ | 1.3k | — | ~8.7k | Automated safety check: Notes | MIT | 2 days ago |
| 9 | Check that a code sample, API signature, default, or behavior claim in the docs is actually true, by running it or reading the product source. | langchain-ai/ | 426 | — | ~1.6k | Automated safety check: Pass | MIT | yesterday |
| 10 | Produce a reproducible, sanitized diagnostic bundle for a LangChain / LangGraph incident — environment snapshot, version manifest, filtered astreamevents(v2) transcript, propagating callback stack… | jeremylongshore/ | 2.8k | — | ~4.6k | Automated safety check: Pass | MIT | yesterday |
| 11 | Build reproducible evaluation pipelines for LangChain 1.0 chains and LangGraph 1.0 agents — golden datasets, LangSmith evaluate(), ragas RAG metrics, deepeval LLM-as-judge, agent trajectory… | jeremylongshore/ | 2.8k | — | ~3.7k | Automated safety check: Pass | MIT | yesterday |
| 12 | Wire LangSmith tracing and custom metric callbacks into a LangChain 1.0 chain or LangGraph 1.0 agent correctly — env-var spelling, subgraph propagation, per-tenant dimensions, cost and latency… | jeremylongshore/ | 2.8k | — | ~3.9k | Automated safety check: Notes | MIT | yesterday |